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plyr

plyr is a set of tools for a common set of problems: you need to split up a big data structure into homogeneous pieces, apply a function to each piece and then combine all the results back together. For example, you might want to:

  • fit the same model each patient subsets of a data frame
  • quickly calculate summary statistics for each group
  • perform group-wise transformations like scaling or standardising

It's already possible to do this with base R functions (like split and the apply family of functions), but plyr makes it all a bit easier with:

  • totally consistent names, arguments and outputs
  • convenient parallelisation through the foreach package
  • input from and output to data.frames, matrices and lists
  • progress bars to keep track of long running operations
  • built-in error recovery, and informative error messages
  • labels that are maintained across all transformations

Considerable effort has been put into making plyr fast and memory efficient, and in many cases plyr is as fast as, or faster than, the built-in equivalents.

A detailed introduction to plyr has been published in JSS: "The Split-Apply-Combine Strategy for Data Analysis", http://www.jstatsoft.org/v40/i01/. You can find out more at http://had.co.nz/plyr/, or track development at http://github.com/hadley/plyr. You can ask questions about plyr (and data manipulation in general) on the plyr mailing list. Sign up at http://groups.google.com/group/manipulatr.

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Install

install.packages('plyr')

Monthly Downloads

385,900

Version

1.8.4

License

MIT + file LICENSE

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Maintainer

Last Published

June 8th, 2016

Functions in plyr (1.8.4)

as.data.frame.function

Make a function return a data frame.
arrange

Order a data frame by its colums.
a_ply

Split array, apply function, and discard results.
amv_dimnames

Dimension names.
as.quoted

Convert input to quoted variables.
alply

Split array, apply function, and return results in a list.
amv_dim

Dimensions.
aaply

Split array, apply function, and return results in an array.
adply

Split array, apply function, and return results in a data frame.
as.list.split

Convert split list to regular list.
ddply

Split data frame, apply function, and return results in a data frame.
defaults

Set defaults.
d_ply

Split data frame, apply function, and discard results.
create_progress_bar

Create progress bar.
eval.quoted

Evaluate a quoted list of variables.
here

Capture current evaluation context.
empty

Check if a data frame is empty.
dlply

Split data frame, apply function, and return results in a list.
dims

Number of dimensions.
id

Compute a unique numeric id for each unique row in a data frame.
is.formula

Is a formula? Checks if argument is a formula
idata.frame

Construct an immutable data frame.
count

Count the number of occurences.
join_all

Recursively join a list of data frames.
l_ply

Split list, apply function, and discard results.
join.keys

Join keys. Given two data frames, create a unique key for each row.
desc

Descending order.
baseball

Yearly batting records for all major league baseball players
indexed_df

An indexed data frame.
indexed_array

An indexed array.
colwise

Column-wise function.
compact

Compact list.
join

Join two data frames together.
daply

Split data frame, apply function, and return results in an array.
liply

Experimental iterator based version of llply.
laply

Split list, apply function, and return results in an array.
m_ply

Call function with arguments in array or data frame, discarding results.
list_to_vector

List to vector.
list_to_array

List to array.
[.split

Subset splits.
mapvalues

Replace specified values with new values, in a vector or factor.
mutate

Mutate a data frame by adding new or replacing existing columns.
name_rows

Toggle row names between explicit and implicit.
match_df

Extract matching rows of a data frame.
names.quoted

Compute names of quoted variables.
plyr-deprecated

Deprecated Functions in Package plyr
mdply

Call function with arguments in array or data frame, returning a data frame.
ozone

Monthly ozone measurements over Central America.
nunique

Number of unique values.
id_var

Numeric id for a vector.
.

Quote variables to create a list of unevaluated expressions for later evaluation.
progress_win

Graphical progress bar, powered by Windows.
each

Aggregate multiple functions into a single function.
quickdf

Quick data frame.
failwith

Fail with specified value.
progress_none

Null progress bar
print.split

Print split.
rbind.fill

Combine data.frames by row, filling in missing columns.
raply

Replicate expression and return results in a array.
plyr

plyr: the split-apply-combine paradigm for R.
print.quoted

Print quoted variables.
rename

Modify names by name, not position.
revalue

Replace specified values with new values, in a factor or character vector.
round_any

Round to multiple of any number.
splitter_a

Split an array by .margins.
take

Take a subset along an arbitrary dimension
vaggregate

Vector aggregate.
summarise

Summarise a data frame.
try_default

Try, with default in case of error.
rdply

Replicate expression and return results in a data frame.
rbind.fill.matrix

Bind matrices by row, and fill missing columns with NA.
reduce_dim

Reduce dimensions.
tryapply

Apply with built in try. Uses compact, lapply and tryNULL
split_labels

Generate labels for split data frame.
unrowname

Un-rowname.
is.discrete

Determine if a vector is discrete.
loop_apply

Loop apply
isplit2

Split iterator that returns values, not indices.
maply

Call function with arguments in array or data frame, returning an array.
llply

Split list, apply function, and return results in a list.
ldply

Split list, apply function, and return results in a data frame.
list_to_dataframe

List to data frame.
mlply

Call function with arguments in array or data frame, returning a list.
progress_tk

Graphical progress bar, powered by Tk.
progress_text

Text progress bar.
progress_time

Text progress bar with time.
rlply

Replicate expression and return results in a list.
r_ply

Replicate expression and discard results.
true

Function that always returns true.
splat

`Splat' arguments to a function.
split_indices

Split indices.
splitter_d

Split a data frame by variables.
strip_splits

Remove splitting variables from a data frame.